Topological Data Analysis for Railway Track Geometry Safety and Maintenance
Petros Woldemariam, Nii Attoh-Okine · Journal of Computing in Civil Engineering · 2025
This paper explores the use of topological data analysis (TDA) to improve railway track geometry, focusing on enhancing safety and maintenance. It uses methods such as Betti numbers, homology, and the Mapper algorithm to understand the shape and connections within the geometry data. The focus of this paper is on persistent homology and the Mapper algorithm, which reveal consistent patterns and gaps in data. The research emphasizes TDA’s practical implications for railway maintenance and monitoring, advocating for its integration into railway engineering practices to address challenges and improve system performance. It points to future possibilities for using TDA in railway engineering, providing some suggestions and better tools needed to take full advantage of TDA’s benefits for railway safety.